Clusteval logo ClustEval clustering evaluation framework

Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 1.0 metric=euclidean
k=261
samples=20
Clustering
Self Organizing Maps 1.0 x=105
y=21
Clustering
Spectral Clustering 1.0 k=84 Clustering
clusterdp 1.0 k=6
dc=10.10258492774113
Clustering
HDBSCAN 1.0 minPts=3
k=76
Clustering
AGNES 1.0 method=complete
metric=euclidean
k=54
Clustering
c-Means 1.0 k=139
m=5.0
Clustering
k-Medoids (PAM) 1.0 k=66 Clustering
DIANA 1.0 metric=euclidean
k=134
Clustering
DBSCAN 1.0 eps=0.0
MinPts=11
Clustering
Hierarchical Clustering 1.0 method=complete
k=235
Clustering
fanny 1.0 k=148
membexp=2.0
Clustering
k-Means 1.0 k=188
nstart=10
Clustering
DensityCut 1.0 alpha=0.01984126984126984
K=7
Clustering
clusterONE 0.0 s=104
d=0.8
Clustering
Affinity Propagation 1.0 dampfact=0.845
preference=30.307754783223388
maxits=5000
convits=425
Clustering
Markov Clustering 0.0 I=8.182582582582583 Clustering
Transitivity Clustering 1.0 T=26.84921219534805 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=F
Clustering